Model updates #1409
Model updates #1409
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kaustubh-darekar
requested review from
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prakriti-solankey and
praveshkumar1988
…into model_updates
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Pull request overview
Copilot reviewed 16 out of 17 changed files in this pull request and generated 5 comments.
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| elif embedding_model_name == "titan": | ||
| embeddings = get_bedrock_embeddings() | ||
| dimension = 1536 | ||
| dimension = 1024 |
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The embedding dimension for the Bedrock Titan model is changed from 1536 to 1024. However, Amazon Titan Text Embeddings v1 produces 1536-dimensional embeddings, while v2 produces 1024-dimensional embeddings. The comment on line 52 of example.env mentions amazon.titan-embed-text-v2.0, which would have 1024 dimensions. Please ensure this dimension matches the actual Titan model version being used by the get_bedrock_embeddings() function.
| ENTITY_EMBEDDING="TRUE" # TRUE or FALSE based on whether to create embeddings for entities suitable for entity vector mode | ||
| DUPLICATE_SCORE_VALUE =0.97 | ||
| DUPLICATE_TEXT_DISTANCE =3 | ||
| DEFAULT_DIFFBOT_CHAT_MODEL="openai_gpt_4o" #whichever model specified here , need to add config for that model in below format) |
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The DEFAULT_DIFFBOT_CHAT_MODEL is set to openai_gpt_4o, which is a model that was removed in this PR. This creates an inconsistency - the default references a model that may not be configured. Consider updating this to one of the new models like openai_gpt_5_mini or another valid model that's included in the updated model list.
| DEFAULT_DIFFBOT_CHAT_MODEL="openai_gpt_4o" #whichever model specified here , need to add config for that model in below format) | |
| DEFAULT_DIFFBOT_CHAT_MODEL="openai_gpt_5_mini" #whichever model specified here , need to add config for that model in below format) |
| process.env?.VITE_LLM_MODELS?.trim() != '' | ||
| ? (process.env.VITE_LLM_MODELS?.split(',') as string[]) |
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The condition process.env?.VITE_LLM_MODELS?.trim() != '' is potentially incorrect. If process.env.VITE_LLM_MODELS is undefined, calling .trim() will throw an error before the comparison. The previous condition checked for truthiness first. Consider using: process.env?.VITE_LLM_MODELS?.trim() (with optional chaining continuing) or process.env.VITE_LLM_MODELS && process.env.VITE_LLM_MODELS.trim() != ''.
| process.env?.VITE_LLM_MODELS?.trim() != '' | |
| ? (process.env.VITE_LLM_MODELS?.split(',') as string[]) | |
| process.env.VITE_LLM_MODELS && process.env.VITE_LLM_MODELS.trim() !== '' | |
| ? (process.env.VITE_LLM_MODELS.split(',') as string[]) |
| return (url.trim() != '' && /(http(s)?:\/\/.)?(www\.)?[-a-zA-Z0-9@:%._~#=]{2,256}\.[a-z]{2,6}\b([-a-zA-Z0-9@:%_.~#?&//=]*)/g.test(url) != false); | ||
| return ( | ||
| url.trim() != '' && | ||
| /(http(s)?:\/\/.)?(www\.)?[-a-zA-Z0-9@:%._~#=]{2,256}\.[a-z]{2,6}\b([-a-zA-Z0-9@:%_.~#?&//=]*)/g.test(url) != false |
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Character '/' is repeated in the same character class.
| # is_gemini_enabled = os.environ.get("GEMINI_ENABLED", "False").lower() in ("true", "1", "yes") | ||
| # if is_gemini_enabled: | ||
| # add_routes(app,ChatVertexAI(), path="/vertexai") |
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| # is_gemini_enabled = os.environ.get("GEMINI_ENABLED", "False").lower() in ("true", "1", "yes") | |
| # if is_gemini_enabled: | |
| # add_routes(app,ChatVertexAI(), path="/vertexai") |
Updating models to latest version
Updating embedding model and their dimensions parameter.
Updating integration test script
Updating other dependent codes